|Chappell, Adrian - UNIV. OF SALFORD, UK|
|Brunner, Gilly - UNIV. OF SALFORD, UK|
Submitted to: Earth Surface Processes and Landforms
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: February 23, 2004
Publication Date: February 23, 2004
Citation: Chappell, A., Zobeck, T.M., Brunner, G. 2003. Induced soil surface changes detected using nadir spectral reflectance to characterise soil erodibility.. Earth Surface Processes and Landforms. Interpretive Summary: Computer models used to predict wind erosion consider the vulnerability of the soil surface to the effects of the wind. Many studies have shown that small changes in soil surface properties can have a great impact on dust emitted during a dust storm. Since, soil properties often change very rapidly in time and in space, methods to rapidly determine soil properties considered important in the wind erosion process in time and space are needed. In this study, we used the reflectance of the soil surface, measured by sensors above the soil surface, to determine changes in the soil surface. Three soil surfaces were changed using artificial rainfall and wind tunnel abrasion procedures. The reflectance of the soil surface was observed after no disturbance and after the rainfall or abrasion was performed. We were successful in measuring the crust and loose erodible material on the crust caused by the rainfall tests. In addition, we were successful in detecting different levels of abrasion of crusted soils. In this study, we identified how the patterns of reflectance changed with each treatment. Although much work still needs to be done, this study demonstrates that remote sensing of soil reflectance has great potential in detecting small changes in surface soil properties needed to predict wind erosion.
Technical Abstract: The surface susceptibility to erosion (erodibility) is an important component of soil erosion models. Many studies of wind erosion have shown that even relatively small changes in surface conditions can have a considerable effect on the temporal and spatial variability of dust emissions. One of the main difficulties in measuring erodibility is that it is controlled by a number of highly variable soil factors. Collection of these data is often limited in scale because in situ measurements are labour-intensive and very time-consuming. To improve wind erosion model predictions over several spatial and temporal scales simultaneously, there is a requirement for a non-invasive approach that can be used to rapidly assess changes in the compositional and structural nature of a soil surface in time and space. Spectral reflectance of the soil surface appears to meet these desirable requirements and it is controlled by properties that affect the soil erodibility. Three soil surfaces were modified using rainfall simulation and wind tunnel abrasion experiments. Observations of those changes were made and recorded using digital images and on-nadir spectral reflectance. The results showed clear evidence of the information content in the spectral domain that was otherwise difficult to interpret given the complicated interrelationships between soil composition and structure. Changes detected at the soil surface included the presence of a crust produced by rainsplash, the production of loose erodible material covering a rain crust and the selective erosion of the soil surface. The effect of rainsplash and aeolian abrasion was different for each soil tested and crust abrasion was shown to decrease as rainfall intensity increased. The relative contributions of the eroded material from each soil surface to trapped mixtures of material assisted the erodibility assessment. Ordination analyses within each of two important soil types explained significant amounts of the variation in the reflectance of all wavebands by treatments of the soil and hence changes in the soil surface. It is likely that the variation in environmental treatments within a soil type is an underestimated source of variation in the characterisation of soil surface erodibility and in the remote sensing of soil.